Compressive sensing aided seismic geometry design for offshore acquisition

• Autorzy: Huang, Xiaogang , Zhang, Jinmiao , Du, Xiangdong , Zhu, Zhenyu , Li, Weixin , Zhang, Yiming , Ding, Jicai , Liu, Zhipeng , Zhang, Jianfeng
• Języki publikacji: EN

Abstrakty

EN

Seismic acquisition guided by the compressive sensing theory can significantly improve seismic data acquisition efficiency and reduce the cost. After reviewing the basic principles of compressive sensing, we propose an optimized random sampling method that can control the maximum sampling interval and improve the design flexibility. We analyze several factors that can introduce reconstruction errors from compressive sensed data and learn that besides sampling method, reconstruction errors increase with decimation degree and the complexity of structures and also depend on the reconstruction workflow. In addition, we provide a basic workflow of the geometry design of compressive sensing acquisition. We analyze the feasibility of the three types of receiving equipment that are widely used in marine environment and discuss the potential cost reduction and efficiency gain. Our field example demonstrates the detailed working process and the feasibility of the combination of random sailing line intervals and random shot intervals and verifies the effect of cost saving and efficiency increasing.

Słowa kluczowe

PL

oszczędne próbkowanie; próbkowanie losowe; obniżenie kosztów; zwiększenie wydajności

EN

compressive sensing; random sampling; reducing costs; increasing efficiency; high-efficiency acquisition

• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 2
• Strony: 547--562
• Opis fizyczny: Bibliogr. 33 poz.

Twórcy

autor

Huang, Xiaogang

• CNOOC Research Institute Ltd., Beijing 100028, China,

autor

Zhang, Jinmiao

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Du, Xiangdong

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Zhu, Zhenyu

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Li, Weixin

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Zhang, Yiming

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Ding, Jicai

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Liu, Zhipeng

• CNOOC Research Institute Ltd., Beijing 100028, China

autor

Zhang, Jianfeng

• Tianjin Branch, CNOOC China Limited, Tianjin 300450, China

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Identyfikatory

DOI

10.1007/s11600-022-00748-0